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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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International Journal of Fuzzy Logic and Intelligent Systems
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Journal DOI :
Korean Institute of Intelligent Systems
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Volume & Issues
Volume 6, Issue 4 - Dec 2006
Volume 6, Issue 3 - Sep 2006
Volume 6, Issue 2 - Jun 2006
Volume 6, Issue 1 - Mar 2006
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A Machine Vision System for Inspecting Tape-Feeder Operation
Cho Tai-Hoon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 95~99
DOI : 10.5391/IJFIS.2006.6.2.095
A tape feeder of a SMD(Surface Mount Device) mounter is a device that sequentially feeds electronic components on a tape reel to the pick-up system of the mounter. As components are getting much smaller, feeding accuracy of a feeder becomes one of the most important factors for successful component pick-up. Therefore, it is critical to keep the feeding accuracy to a specified level in the assembly and production of tape feeders. This paper describes a tape feeder inspection system that was developed to automatically measure and to inspect feeding accuracy using machine vision. It consists of a feeder base, an image acquisition system, and a personal computer. The image acquisition system is composed of CCD cameras with lens, LED illumination systems, and a frame grabber inside the PC. This system loads up to six feeders at a time and inspects them automatically and sequentially. The inspection software was implemented using Visual C++ on Windows with easily usable GUI. Using this system, we can automatically measure and inspect the quality of ail feeders in production process by analyzing the measurement results statistically.
A New Class of Similarity Measures for Fuzzy Sets
Omran Saleh ; Hassaballah M. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 100~104
DOI : 10.5391/IJFIS.2006.6.2.100
Fuzzy techniques can be applied in many domains of computer vision community. The definition of an adequate similarity measure for measuring the similarity between fuzzy sets is of great importance in the field of image processing, image retrieval and pattern recognition. This paper proposes a new class of the similarity measures. The properties, sensitivity and effectiveness of the proposed measures are investigated and tested on real data. Experimental results show that these similarity measures can provide a useful way for measuring the similarity between fuzzy sets.
Analyzing the Effect of Lexical and Conceptual Information in Spam-mail Filtering System
Kang Sin-Jae ; Kim Jong-Wan ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 105~109
DOI : 10.5391/IJFIS.2006.6.2.105
In this paper, we constructed a two-phase spam-mail filtering system based on the lexical and conceptual information. There are two kinds of information that can distinguish the spam mail from the ham (non-spam) mail. The definite information is the mail sender's information, URL, a certain spam keyword list, and the less definite information is the word list and concept codes extracted from the mail body. We first classified the spam mail by using the definite information, and then used the less definite information. We used the lexical information and concept codes contained in the email body for SVM learning in the 2nd phase. According to our results the ham misclassification rate was reduced if more lexical information was used as features, and the spam misclassification rate was reduced when the concept codes were included in features as well.
Collaborative filtering based Context Information for Real-time Recommendation Service in Ubiquitous Computing
Lee Se-ll ; Lee Sang-Yong ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 110~115
DOI : 10.5391/IJFIS.2006.6.2.110
In pure P2P environment, it is possible to provide service by using a little real-time information without using accumulated information. But in case of using only a little information that was locally collected, quality of recommendation service can be fallen-off. Therefore, it is necessary to study a method to improve qualify of recommendation service by using users' context information. But because a great volume of users' context information can be recognized in a moment, there can be a scalability problem and there are limitations in supporting differentiated services according to fields and items. In this paper, we solved the scalability problem by clustering context information per each service field and classifying it per each user, using SOM. In addition, we could recommend proper services for users by quantifying the context information of the users belonging to the similar classification to the service requester among classified data and then using collaborative filtering.
Color Edge Detection using Variable Template Operator
Baek Young-Hyun ; Moon Sung-Ryong ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 116~120
DOI : 10.5391/IJFIS.2006.6.2.116
This paper discusses an approach for detecting a new edge in color images. The color image is to be represented by a vector field, and the color image edges are detected as differences in the local vector statistics. This method is based on the calculation for the vector angle between two adjacent pixels. Unlike Euclidean distance in RGB space, the vector angle distinguishes the differences in chromaticity, independent of luminance or intensity. The proposed approach can easily accommodate concepts, such as variable template edge detection, as well as the latest developments in vector order statistics for color image processing. In this paper, it is used not a conventional fixed template operator but a variable template operator The variable template is implemented and experimental results for digital color images are included.
Fuzzy Skyhook Control of A Semi-active Suspension System
Cho Jeong-Mok ; Jung Tae-Geun ; Joh Joong-Seon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 121~126
DOI : 10.5391/IJFIS.2006.6.2.121
In the recent years, the development of computer-controlled suspension dampers and actuators has improved the trade-off between the vehicle handling and ride comfort, and has led to the development of various damper control policies. The skyhook control is an effective control strategy for suppressing vehicle vibration. In this study, a fuzzy skyhook control is proposed and tuned by a genetic algorithm to improve ride comfort. The proposed fuzzy skyhook control is applied to a quarter-car model in order to compare its performance with continuous skyhook suspensions. To obtain optimized fuzzy skyhook control, scale factors and in-out membership functions are tuned by a genetic algorithm. The simulation results show that the fuzzy skyhook control offers more effective suspension performance over the continuous skyhook control.
H-infinity Discrete Time Fuzzy Controller Design Based on Bilinear Matrix Inequality
Chen M. ; Feng G. ; Zhou S.S. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 127~137
DOI : 10.5391/IJFIS.2006.6.2.127
This paper presents an
controller synthesis method for discrete time fuzzy dynamic systems based on a piecewise smooth Lyapunov function. The basic idea of the proposed approach is to construct controllers for the fuzzy dynamic systems in such a way that a Piecewise smooth Lyapunov function can be used to establish the global stability with
performance of the resulting closed loop fuzzy control systems. It is shown that the control laws can be obtained by solving a set of Bilinear Matrix Inequalities (BMIs). An example is given to illustrate the application of the proposed method.
Optimal Fuzzy Models with the Aid of SAHN-based Algorithm
Lee Jong-Seok ; Jang Kyung-Won ; Ahn Tae-Chon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 138~143
DOI : 10.5391/IJFIS.2006.6.2.138
In this paper, we have presented a Sequential Agglomerative Hierarchical Nested (SAHN) algorithm-based data clustering method in fuzzy inference system to achieve optimal performance of fuzzy model. SAHN-based algorithm is used to give possible range of number of clusters with cluster centers for the system identification. The axes of membership functions of this fuzzy model are optimized by using cluster centers obtained from clustering method and the consequence parameters of the fuzzy model are identified by standard least square method. Finally, in this paper, we have observed our model's output performance using the Box and Jenkins's gas furnace data and Sugeno's non-linear process data.
Parametric Design on Bellows of Piping System Using Fuzzy Knowledge Processing
Lee Yang-Chang ; Lee Joon-Seong ; Choi Yoon-Jong ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 144~149
DOI : 10.5391/IJFIS.2006.6.2.144
This paper describes a novel automated analysis system for bellows of piping system. An automatic finite element (FE) mesh generation technique, which is based on the fuzzy theory and computational geometry technique, is incorporated into the system, together with one of commercial FE analysis codes and one of commercial solid modelers. In this system, a geometric model, i.e. an analysis model, is first defined using a commercial solid modelers for 3-D shell structures. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Delaunay triangulation technique is introduced as a basic tool for element generation. The triangular elements are converted to quadrilateral elements. Practical performances of the present system are demonstrated through several analysis for bellows of piping system.
Pattern Recognition Methods for Emotion Recognition with speech signal
Park Chang-Hyun ; Sim Kwee-Bo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 150~154
DOI : 10.5391/IJFIS.2006.6.2.150
In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.
Robust Indirect Adaptive Fuzzy Controller for Balancing and Position Control of Inverted Pendulum System
Kim Yong-Tae ; Kim Dong-Yon ; Yoo Jae-Ha ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 155~160
DOI : 10.5391/IJFIS.2006.6.2.155
In the paper a robust indirect adaptive fuzzy controller is proposed for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the proposed fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing and a supervisory fuzzy controller which emulates heuristic control strategy and arbitrate two control objectives. It is proved that the signals in the overall system are bounded. Simulation results are given to verify the proposed adaptive fuzzy control method.
Simultaneous Localization and Mobile Robot Navigation using a Sensor Network
Jin Tae-Seok ; Bashimoto Hideki ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 161~166
DOI : 10.5391/IJFIS.2006.6.2.161
Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.
Systematic Elicitation of Proximity for Context Management
Kim Chang-Suk ; Lee Sang-Yong ; Son Dong-Cheul ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 167~172
DOI : 10.5391/IJFIS.2006.6.2.167
As ubiquitous devices are fast spreading, the communication problem between humans and these devices is on the rise. The use of context is important in interactive application such as handhold and ubiquitous computing. Context is not crisp data, so it is necessary to introduce the fuzzy concept. The proxity relation is represented by the degree of closeness or similarity between data objects of a scalar domain. A context manager of context-awareness system evaluates imprecise queries with the proximity relations. in this paper, a systematic proximity elicitation method are proposed. The proposed generation method is simple and systematic. It is based on the well-known fuzzy set theory and applicable to the real world applications because it has tuning parameter and weighting factor. The proposed representations of proximity relation is more efficient than the ordinary matrix representation since it reflects some properties of a proximity relation to save space. We show an experiments of quantitative calculate for the proximity relation. And we analyze the time complexity and the space occupancy of the proposed representation method.
The network model for Detection Systems based on data mining and the false errors
Lee Se-Yul ; Kim Yong-Soo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 6, issue 2, 2006, Pages 173~177
DOI : 10.5391/IJFIS.2006.6.2.173
This paper investigates the asymmetric costs of false errors to enhance the detection systems performance. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of probe detection is enhanced by considering the costs of false errors.